Machine Learning and Data Analytics for Solving Business Problems Methods, Applications, and Case Studies

This book presents advances in business computing and data analytics by discussing recent and innovative machine learning methods that have been designed to support decision-making processes. These methods form the theoretical foundations of intelligent management systems, which allows for companies...

Full description

Bibliographic Details
Other Authors: Alyoubi, Bader (Editor), Ben Ncir, Chiheb-Eddine (Editor), Alharbi, Ibraheem (Editor), Jarboui, Anis (Editor)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2022, 2022
Edition:1st ed. 2022
Series:Unsupervised and Semi-Supervised Learning
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Description
Summary:This book presents advances in business computing and data analytics by discussing recent and innovative machine learning methods that have been designed to support decision-making processes. These methods form the theoretical foundations of intelligent management systems, which allows for companies to understand the market environment, to improve the analysis of customer needs, to propose creative personalization of contents, and to design more effective business strategies, products, and services. This book gives an overview of recent methods – such as blockchain, big data, artificial intelligence, and cloud computing – so readers can rapidly explore them and their applications to solve common business challenges. The book aims to empower readers to leverage and develop creative supervised and unsupervised methods to solve business decision-making problems. Provides design and applications of machine learning and data analytics to solve business problems; Includes applications of supervised and unsupervised learning methods in intelligent management systems; Introduces case studies of business problems solved using innovative learning methods and data analytics techniques
Physical Description:XII, 206 p. 50 illus., 38 illus. in color online resource
ISBN:9783031184833